Right now, nearly every company I speak with is convinced they’re facing an AI crisis. Their AI drafts outreach emails that never get a reply. It “researches” accounts and flags opportunities the sales team actually closed half a year ago. Endless hours of copying and pasting between tools churn out content that sounds indistinguishable from what every rival is already publishing. Executives keep buying new tools, scheduling more trainings, and still end up asking the same question: why isn’t AI making a real impact? Here’s what usually gets left out. The issue isn’t your model. It isn’t your data. The real blocker is context: the concrete, up‑to‑date understanding of your business, your customers and their current needs, and the way your team truly operates. It’s also the toughest challenge to tackle—and the one the industry has been slowest to confront. Context is the Infrastructure, Not the Feature Here’s the nuance I see getting missed. Data is what happened. Context explains those events—what they signify, why they matter, and what action they should trigger. Context isn’t a nice-to-have feature; it’s foundational infrastructure. Your CRM might show that a deal closed eighteen months ago. That’s data. Context is knowing it closed because your champion moved to a new company, pricing had to be revised three separate times, and that customer now sends you several referrals a year and despises automated outreach. A human who owned that account understands all of…